Serotonin and beyond: therapeutics for major depression
Bibliographic record
Abstract
The serotonin (5-HT, 5-hydroxytryptamine) system has been implicated in the pathogenesis of major depressive disorder (MDD). The case for its contribution to the therapeutic efficacy of a wide variety of antidepressant treatments is, however, much stronger. All antidepressant strategies have been shown to enhance 5-HT transmission in the brain of laboratory animals. Catecholamines, norepinephrine (NE) and dopamine (DA) can also play a pivotal role in the mechanism of action of certain antidepressant strategies. The enhancement of 5-HT transmission by selective serotonin reuptake inhibitors, which leads to a dampening of the activity of NE and DA neurons, may account in part for the low remission rate achieved with these medications and/or the residuals symptoms after remission is achieved. The functional connectivity between the 5-HT, NE and DA systems can be used to understand the mechanism of action of a wide variety of augmentation strategies in treatment-resistant MDD. Proof-of-concept studies have shown that antidepressant medications with complementary mechanisms of action on monoaminergic systems can double the remission rate achieved in a trial of standard duration. Novel approaches are also being used to treat MDD, which also appear to involve the monoaminergic system(s) to a varying extent.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".